This dataset provides stream networks for three river basins in eastern Sri Lanka (Mundeni Aru, Maduru Oya and Miyangolla Ela). The stream networks were developed for use in hydrologic modelling and are provided as shapefiles. The work was supported by the Natural Environment Research Council (Grant NE/S005838/1). Full details about this dataset can be found at https://doi.org/10.5285/0537af26-5cab-4381-aca0-d997db421111

This dataset details the allometry and leaf trait measurements in three common gardens of fifteen juvenile tree species from the Colombian Andes planted along a thermosequence (14, 22 and 26 deg C) in the Antioquia region of Colombia. Allometric data includes tree diameter at the base, total tree height and height to the first branch, crown diameters, health status, survival and percentage of herbivory attacks over ten measuring campaigns from February 2019 until January 2022. Trait data includes leaf area, thickness, dry weight, leaf mass per area total number of branches and leaves per tree. Regarding the common garden plantations the trees were planted in the ground between November 2019 and January 2019 with planting height ranging between 50 and 100 cm (species dependent). Full details about this dataset can be found at https://doi.org/10.5285/c7ce1610-aba3-4a09-bf7c-1b6c774d597a

[This application is embargoed until January 1, 2025]. A collection of python and bash scripts to implement, train and deploy a generative adversarial network for population genetic inferences. The networks have been tuned to be deployed to genomic data from Anopheles mosquitoes. However, the general framework can be applied to other species. It requires the input data to be in Variant Call Format (VCF) format and the simulations need to be in msprime format. Full details about this application can be found at https://doi.org/10.5285/3ae572f6-4862-47ae-b4a0-4b9c496b5b54

This dataset details information collected from smallholder oil palm farms in Sabah, Malaysian Borneo. Including: management practices, oil palm fruit yield, understorey vegetation, and soil chemical properties (SOC, total N, total P and available P). We collected data between August to November 2019 from 40 smallholdings (defined as farms < 50 ha) across six governance areas in Sabah. We used responses from face-to-face questionnaires to collect information about their management practices, including Best Management Practices (BMPs), and reported Fresh Fruit Bunch (FFB) yields. We also carried out field surveys on these farms to quantify vegetation cover and soil chemical properties. All smallholder farms had mature fruiting trees i.e. > 8 years since planting. The project received ethical approval from the Biology Ethics Committee, University of York (Ref. SGA201906), and permission from the Sabah Biodiversity Council (Ref. JKM/MBS.1000-2/2 JLD.8), Danum Valley Management Committee (Ref. YS/DVMC/2019/27), and South East Asia Rainforest Research Partnership (project number 18033) for permission to conduct our research in Sabah, Malaysia. This work was funded by the NERC iCASE studentship (NE/R007624/1) and Proforest. Full details about this dataset can be found at https://doi.org/10.5285/38487932-b32a-4b15-9fda-ea812c463466

Elemental analysis of 80 soil samples taken in the Ningbo Watershed, in the Zhangxi catchment, Eastern China. Variables measured include As, Cd, Cr, Cu, Ni, P, Pb, and lead isotope ratios along with concentrations of Zn, Ca and K. Data was collected in March 2016 and analysed at Queens Belfast University. The data was collected and analysed as part of a NERC NSFC funded multi project research programme UK- China Critical Zone Observation Programme. Full details about this dataset can be found at https://doi.org/10.5285/9c2e8b85-48ab-48c9-b69d-dd676a5d086f

The dataset contains borehole groundwater levels and physico-chemical parameters for the period May 2017 to June 2018 including; (1) near-monthly measurements of water table depth, groundwater temperature, pH, electrical conductivity and total dissolved solids obtained from manual sampling of 22 boreholes; and (2) higher temporal resolution (5-min time-step) timeseries of water table depth, groundwater temperature and electrical conductivity obtained from automatic dataloggers in 3 of the abovementioned boreholes. Full details about this dataset can be found at https://doi.org/10.5285/40a80d95-5a8a-4586-aa24-d6c87f9968b6

The dataset provides transcripts from focus groups in Salima, Mangochi and Zomba (Malawi). The focus groups' discussions focused on important monthly agricultural activities in association with the climate services and extreme weather events. This outlined how climatic factors affected agricultural decision-making. The data were produced as part of NERC Program Science for Humanitarian Emergencies and Resilience (SHEAR). Grant reference - Improving Preparedness to Agro-Climatic Extremes in Malawi (IPACE-Malawi). Full details about this dataset can be found at https://doi.org/10.5285/199b0046-79a3-4e74-8152-17f10c376671

The dataset delineates annual forest loss in the CAZ digitized from annual 15 metre resolution LANDSAT imagery. This dataset creates a baseline for possible long-term, near real-time monitoring of encroachment and illegal logging within the Ankeniheny-Zahamena Corridor (CAZ), Madagascar. This analysis includes a summary of suspected encroachment and illegal logging from June 2006 to December 2010 within the "protected area," which consists of zones such as priority for conservation, sustainable use, and controlled settlements. Full details about this dataset can be found at https://doi.org/10.5285/c63c543f-3e95-4c1c-8c69-12f942271813

This dataset contains the results of a farmers’ survey in the Ping Catchment in Thailand. The aim of this survey was to identify the specific socioeconomic impacts that historical droughts in the Ping catchment have had for agricultural communities, and identify factors affecting adaptation decisions, as well as analyse the communications with and amongst farmers at the local scale in the Ping catchment during drought. Villages in the Ping catchment with a history of drought were selected to represent typical agricultural production typologies. In total, 176 questionnaires were completed with a close to even distribution of respondents coming from the provinces of Chiang Mai (n=41), Lamphun (n=45), Kamphaeng Phet (n=45) and Tak (n=45). Full details about this dataset can be found at https://doi.org/10.5285/155e1867-bc9d-44f0-9f85-0f682964f720

This model code for object oriented data analysis of surface motion time series in peatland landscapes provides the procedure to assess peatland condition using object oriented data analysis. The model code assesses peatland condition according to which cluster each surface motion time series is assigned, based on key measures capturing differences between the time series. It can be run on any machine with R. Full details about this application can be found at https://doi.org/10.5285/dbdb9f19-c039-4a73-b590-e1acc7f79df4